Anomalous moisture diffusion in an epoxy adhesive detected by magnetic resonance imaging
Bibliographic record
Abstract
Abstract Non‐Fickian or anomalous diffusion is frequently observed when the absorption of moisture by a polymer is being studied. Different models have been presented in the literature that can accurately predict the trends of the weight‐gain curves. However, it is not always clear which of these models yield good predictions of moisture distribution. This article presents a time‐resolved moisture distribution study of an epoxy sample immersed in deuterated water (D 2 O) at 70°C over a period of 2.5 months. The moisture distribution was measured during that period with a novel high‐resolution magnetic resonance imaging technique that is well adapted to the imaging of thin plates. The experimental results showed that the concentration of D 2 O at the surface of the sample increased with time, even after 2.5 months. These results were used to evaluate the performance of several standard diffusion models. Although this study is phenomenological, it appears that a model featuring time‐varying boundary conditions yields the best representation of moisture absorption for these samples. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".